Influence of cationic, anionic, and non-ionic surfactants on in-situ growth of polyaniline on alumina ceramic membranes for the effective crude oil-in-water emulsion separation: Experimental and machine learning approaches

Muhammad Saad Khan, Umair Baig*, Abdul Waheed, Sohaib Abdelazem, Isam H. Aljundi

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

To improve the effectiveness of oil-water separation during produced water (PW) treatment, three types of surfactants (anionic, cationic, and non-ionic) were used in this work to alter in-situ growth of polyaniline (Pani) as an active layer onto an alumina (Al2O3) substrate. This study utilized sodium dodecyl sulfate (SDS), cetyltrimethylammonium bromide (CTAB), and Pluronic F-127 (p-F127) to modify the Pani surface characteristics during an in-situ emulsion polymerization process over an Al2O3 substrate. The most homogeneous and stable active layer growth was observed for the Pani-SDS polymer, which was confirmed by transmission electron microscopy (TEM), high-resolution transmission electron microscopy (HR-TEM), nuclear magnetic resonance (NMR), and thermogravimetric analysis (TGA). The surface morphology, chemical modification, and structural features of the Pani-modified Al2O3 membranes were confirmed using various characterization techniques, including scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), and X-ray diffraction (XRD) diffractograms. The surface wettability of different Pani-modified Al2O3 membranes was also studied, and the results of Pani-SDS@ Al2O3 membrane displayed a high contact angle of 154.1° for oil (super-oleophobic) underwater as opposed to 151.7° for Pani-CTAB@Al2O3 and 149.7° for Pani-p-F-127@Al2O3 membranes. At 2 bar, Pani-SDS@Al2O3 membranes' flux with pure water and permeate flux with crude oil-in-water emulsion were 7292.4 L·m−2·h−1 and 3068.5 L·m−2·h−1, respectively. Pani-SDS@Al2O3 membrane oil-water separation efficiency was significantly higher than the bare Al2O3 and other PANI decorated membranes fabricated in the current study, reaching up to 98.5 %. The strength of the approach is supported by the machine learning models, particularly the SVM, which have achieved an excellent R2 of 0.95 on both permeate flux and separation efficiency. With significant operational and environmental ramifications, this work demonstrates the good potential of Pani-SDS-modified membranes in treating oily wastewater.

Original languageEnglish
Article number119263
JournalDesalination
Volume615
DOIs
StatePublished - 15 Nov 2025

Bibliographical note

Publisher Copyright:
© 2025 Elsevier B.V.

Keywords

  • Machine learning predictions
  • Oil-in-water emulsion separation
  • Polyaniline-modified membranes
  • Surfactants

ASJC Scopus subject areas

  • General Chemistry
  • General Chemical Engineering
  • General Materials Science
  • Water Science and Technology
  • Mechanical Engineering

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